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Examines how impulsive control affects stability in neural networks, indicating potential applications in dynamic systems.
Exponential stability of an impulsive artificial neural network model is investigated using a Lyapunov function. Impulsive control mechanisms, characterized by discrete and sudden interventions, are analyzed for their profound impact on the dynamical behavior of neural networks. It is shown that the stability of the equilibrium depends on the impulse effect.
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Direkçi et al. (2026) studied this question.
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